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Individual cells of the same phenotype are commonly viewed as identical functional units of a tissue or organ. However, the deep sequencing of DNA and RNA from single cells suggests a more complex ecology of heterogeneous cell states that together produce emergent system-level function. Continuing development of high-content, real-time, multimodal single-cell measurement technologies will lead to the ultimate goal of understanding the function of an individual cell in the context of its microenvironment.
Emerging technologies are bringing single-cell genome sequencing into the mainstream; this field has already yielded insights into the genetic architecture and variability between cells that highlight the dynamic nature of the genome.
Recent technical advances have enabled RNA sequencing (RNA-seq) in single cells. Exploratory studies have already led to insights into the dynamics of differentiation, cellular responses to stimulation and the stochastic nature of transcription. We are entering an era of single-cell transcriptomics that holds promise to substantially impact biology and medicine.
Two surveys of over 1,700 publications whose authors use quantitative real-time PCR (qPCR) reveal a lack of transparent and comprehensive reporting of essential technical information. Reporting standards are significantly improved in publications that cite the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines, although such publications are still vastly outnumbered by those that do not.
Optimism about biomedicine is challenged by the increasingly complex ethical, legal and social issues it raises. Reporting of scientific methods is no longer sufficient to address the complex relationship between science and society. To promote 'ethical reproducibility', we call for transparent reporting of research ethics methods used in biomedical research.
Much of what is known about mammalian cell regulation has been achieved with the aid of transiently transfected cells. However, overexpression can violate balanced gene dosage, affecting protein folding, complex assembly and downstream regulation. To avoid these problems, genome engineering technologies now enable the generation of stable cell lines expressing modified proteins at (almost) native levels.
New methods for mapping synaptic connections and recording neural signals generate rich and complex data on the structure and dynamics of brain networks. Making sense of these data will require a concerted effort directed at data analysis and reduction as well as computational modeling.
Opinions diverge on whether mapping the synaptic connectivity of the brain is a good idea. Here we argue that albeit their limitations, such maps will reveal essential characteristics of neural circuits that would otherwise be inaccessible.
By delivering precise, reproducible quantification of proteins of interest in biological samples, targeted proteomics approaches are allowing researchers to apply the scientific method using mass spectrometry.
